Prabukumar Manoharan

1.6k total citations
50 papers, 1.2k citations indexed

About

Prabukumar Manoharan is a scholar working on Media Technology, Atmospheric Science and Computer Vision and Pattern Recognition. According to data from OpenAlex, Prabukumar Manoharan has authored 50 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Media Technology, 25 papers in Atmospheric Science and 16 papers in Computer Vision and Pattern Recognition. Recurrent topics in Prabukumar Manoharan's work include Remote-Sensing Image Classification (31 papers), Remote Sensing and Land Use (25 papers) and Advanced Chemical Sensor Technologies (8 papers). Prabukumar Manoharan is often cited by papers focused on Remote-Sensing Image Classification (31 papers), Remote Sensing and Land Use (25 papers) and Advanced Chemical Sensor Technologies (8 papers). Prabukumar Manoharan collaborates with scholars based in India, Saudi Arabia and United States. Prabukumar Manoharan's co-authors include Shrutika S. Sawant, L. Agilandeeswari, Radhesyam Vaddi, M. Sam Navin, K. Ganesan, Sathishkumar Samiappan, Farhan A. Alenizi, P. Kumaresan, R. Anand and A. K. Mathur and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and International Journal of Remote Sensing.

In The Last Decade

Prabukumar Manoharan

47 papers receiving 1.1k citations

Peers

Prabukumar Manoharan

ECOLO

CVPR

Li Wei China

Dariush Abbasi‐Moghadam Iran

Andrea Marinoni Italy

Tatyana V. Bandos Spain

Liangpei Zhang China

Xia Xu China

Qiong Ran China

Xianghai Cao China

L. Agilandeeswari India

Li Wei China

Prabukumar Manoharan

1.3k ×1.7

842 ×1.5

199 ×0.8

ECOLO

415 ×2.0

CVPR

105 ×0.6

Citations per year, relative to Prabukumar Manoharan Prabukumar Manoharan (= 1×) peers Li Wei

Countries citing papers authored by Prabukumar Manoharan

Since Specialization

Citations

This map shows the geographic impact of Prabukumar Manoharan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Prabukumar Manoharan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Prabukumar Manoharan more than expected).

Fields of papers citing papers by Prabukumar Manoharan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Prabukumar Manoharan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Prabukumar Manoharan. The network helps show where Prabukumar Manoharan may publish in the future.

Co-authorship network of co-authors of Prabukumar Manoharan

This figure shows the co-authorship network connecting the top 25 collaborators of Prabukumar Manoharan. A scholar is included among the top collaborators of Prabukumar Manoharan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Prabukumar Manoharan. Prabukumar Manoharan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Navin, M. Sam, et al.. (2025). Fuzzy Shuffled Frog Leaping Optimization-based enhanced ConvLSTM for Land Use/ Land Cover Prediction. Earth Science Informatics. 18(2). 3 indexed citations

Vaddi, Radhesyam, et al.. (2025). Band selection using oppositional whale optimization for hyperspectral image classification. Vibrational Spectroscopy. 139. 103830–103830. 1 indexed citations

Ghosh, S., et al.. (2025). Novel R-CNN and transformer models for pollution impacts and land cover changes around iconic heritage sites in developing countries: a case study. Scientific Reports. 15(1). 43134–43134.

Navin, M. Sam, L. Agilandeeswari, Prabukumar Manoharan, & Farhan A. Alenizi. (2024). Fuzzy Swin transformer for Land Use/ Land Cover change detection using LISS-III Satellite data. Earth Science Informatics. 17(2). 1745–1764. 18 indexed citations

Vaddi, Radhesyam, et al.. (2024). A new band selection framework for hyperspectral remote sensing image classification. Scientific Reports. 14(1). 31836–31836. 8 indexed citations

Anand, R., Sathishkumar Samiappan, & Prabukumar Manoharan. (2024). Fine-tuning digital FIR filters with gray wolf optimization for peak performance. Scientific Reports. 14(1). 12675–12675. 4 indexed citations

Vaddi, Radhesyam, et al.. (2024). Strategies for dimensionality reduction in hyperspectral remote sensing: A comprehensive overview. The Egyptian Journal of Remote Sensing and Space Science. 27(1). 82–92. 19 indexed citations

Agilandeeswari, L., Prabukumar Manoharan, & Farhan A. Alenizi. (2023). A robust semi-fragile watermarking system using Pseudo-Zernike moments and dual tree complex wavelet transform for social media content authentication. Multimedia Tools and Applications. 82(28). 43367–43419. 19 indexed citations

Agilandeeswari, L., et al.. (2022). Crop Classification for Agricultural Applications in Hyperspectral Remote Sensing Images. Applied Sciences. 12(3). 1670–1670. 76 indexed citations

10.

Sawant, Shrutika S., Prabukumar Manoharan, & Sathishkumar Samiappan. (2020). A modified Cuckoo Search algorithm based optimal band subset selection approach for hyperspectral image classification. SHILAP Revista de lepidopterología. 13 indexed citations

11.

Sawant, Shrutika S. & Prabukumar Manoharan. (2020). A survey of band selection techniques for hyperspectral image classification. SHILAP Revista de lepidopterología. 38 indexed citations

12.

Sawant, Shrutika S. & Prabukumar Manoharan. (2020). A hybrid optimization approach for hyperspectral band selection based on wind driven optimization and modified cuckoo search optimization. Multimedia Tools and Applications. 80(2). 1725–1748. 25 indexed citations

13.

Navin, M. Sam, L. Agilandeeswari, & Prabukumar Manoharan. (2020). Survey on Land Use/Land Cover (LU/LC) change analysis in remote sensing and GIS environment: Techniques and Challenges. Environmental Science and Pollution Research. 27(24). 29900–29926. 132 indexed citations

14.

Kumaresan, P., et al.. (2020). Heuristic approach to minimise the energy consumption of sensors in cloud environment for wireless body area network applications. International Journal of Embedded Systems. 12(4). 475–475. 2 indexed citations

15.

Agilandeeswari, L., et al.. (2019). Facial Emotion Recognition by Deep CNN and HAAR Cascade. International Journal of Innovative Technology and Exploring Engineering. 8(12). 3433–3439. 1 indexed citations

16.

Sawant, Shrutika S. & Prabukumar Manoharan. (2019). New framework for hyperspectral band selection using modified wind-driven optimization algorithm. International Journal of Remote Sensing. 40(20). 7852–7873. 32 indexed citations

17.

Sawant, Shrutika S. & Prabukumar Manoharan. (2018). A review on graph-based semi-supervised learning methods for hyperspectral image classification. The Egyptian Journal of Remote Sensing and Space Science. 23(2). 243–248. 69 indexed citations

18.

Manoharan, Prabukumar, L. Agilandeeswari, & K. Ganesan. (2017). An intelligent lung cancer diagnosis system using cuckoo search optimization and support vector machine classifier. Journal of Ambient Intelligence and Humanized Computing. 10(1). 267–293. 79 indexed citations

19.

Sawant, Shrutika S. & Prabukumar Manoharan. (2017). Semi-supervised techniques based hyper-spectral image classification: A survey. 2017 Innovations in Power and Advanced Computing Technologies (i-PACT). 1–8. 27 indexed citations

20.

Manoharan, Prabukumar, et al.. (2013). An Efficient Scan Conversion of Parabola on Hexagonal Grid. 4(2). 1–8.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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